MPRAsnakeflow experiment QC report

Low correlation warning!

At least one (not all) Spearman correlations across replicates is low using a barcode threshold per oligo of 10! Spearman correlation of DNA is 0.95, RNA is 0.60 and DNA/RNA ratio is 0.65. Minimum allowed values are 0.85, 0.95, and 0.75.

Overall quality metrics

Table explanation

median rna read count: Median of RNA read count for oligos that passed filtering to determine sufficient coverage in terms of read count. Value is the median of all replicates.
median barcodes passing filtering: Median number of barcodes across tested sequences that passed filtering to determine if there was sufficient barcode to oligo coverage. Value is the median of all replicates.
pearson correlation: The correlation of log2 RNA/DNA ratios across tested sequences as a measure of replicable activity signal. Value is the median of replicate comparisons using only oligos with >= 10 barcodes.
fraction oligos passing: Fraction of tested sequences that passed filtering of the mappable sequences to determine if the designed library was sufficiently recovered. Value is the median of all replicates and using only oligos with >= 10 barcodes.

median barcodes passing filtering	median rna read count	pearson correlation	fraction oligos passing
67	641	0.85	0.92

DNA over RNA counts

Plotting normalized counts of DNA vs RNA (median across replicates). Only oligos within all replicates are shown. We should see a variation within the RNA count data (along the y axis). If count data between RNA and DNA is highly correlated (e.g. follows the identity line) there is no variation between designed oligos. This is an indication that RNA is inflated with DNA and the DNA digestion before creating cDNA did not work as expected.

Oligo correlation

Oligo correlation plots of DNA, RNA and DNA/RNA ratios across replicates. First tab shows plots using (in average) 54115 oligos with a minimum number of 10 barcodes. Second tab shows all 58442 oligos that have assigned barcodes.

Condition	A	B	#Oligos A	#Oligos B	#Oligos Joined	DNA spearman	RNA spearman	Ratio spearman	DNA log2 pearson	RNA log2 pearson	Ratio log2 pearson
A549	1	2	54794	54706	54331	0.96	0.63	0.67	0.96	0.82	0.84
A549	1	3	54794	54778	54369	0.96	0.64	0.67	0.96	0.83	0.85
A549	1	4	54794	54341	54069	0.96	0.62	0.67	0.96	0.82	0.84
A549	1	5	54794	54333	54058	0.96	0.60	0.65	0.95	0.81	0.84
A549	2	3	54706	54778	54306	0.96	0.66	0.71	0.96	0.86	0.88
A549	2	4	54706	54341	54047	0.96	0.64	0.70	0.96	0.84	0.86
A549	2	5	54706	54333	54027	0.96	0.63	0.70	0.95	0.84	0.87
A549	3	4	54778	54341	54056	0.96	0.65	0.71	0.96	0.85	0.87
A549	3	5	54778	54333	54063	0.96	0.64	0.70	0.96	0.86	0.87
A549	4	5	54341	54333	53833	0.95	0.61	0.70	0.95	0.84	0.86

Condition	A	B	#Oligos A	#Oligos B	#Oligos Joined	DNA spearman	RNA spearman	Ratio spearman	DNA log2 pearson	RNA log2 pearson	Ratio log2 pearson
A549	1	2	58719	58727	58503	0.95	0.60	0.63	0.91	0.73	0.73
A549	1	3	58719	58717	58482	0.95	0.61	0.64	0.91	0.74	0.74
A549	1	4	58719	58651	58425	0.95	0.59	0.64	0.90	0.71	0.73
A549	1	5	58719	58639	58414	0.95	0.57	0.62	0.90	0.72	0.73
A549	2	3	58727	58717	58498	0.95	0.63	0.67	0.91	0.77	0.77
A549	2	4	58727	58651	58438	0.95	0.61	0.66	0.90	0.74	0.75
A549	2	5	58727	58639	58434	0.95	0.60	0.66	0.90	0.75	0.76
A549	3	4	58717	58651	58428	0.95	0.61	0.67	0.90	0.75	0.76
A549	3	5	58717	58639	58423	0.95	0.61	0.66	0.90	0.77	0.77
A549	4	5	58651	58639	58380	0.94	0.58	0.66	0.90	0.74	0.76

Experiment statistic

The total number of oligos in this experiment is 59308 (defined by the assignment) with 10382452 associated barcodes.

In average across replicates we see 58691 from 4913065 average barcodes in the count data and around 1166025 barcodes where not in the assignment.

condition	replicate	oligos dna/rna	matched barcodes	unknown barcodes dna/rna	% matched barcodes	total dna counts	total rna counts	avg dna counts per bc	avg rna counts per bc	avg dna/rna barcodes per oligo
A549	1	58719	5079064	1199761	80.89	201932147	92956866	32.16	14.80	86.50
A549	2	58727	5001282	1194537	80.72	199108959	100483452	32.14	16.22	85.16
A549	3	58717	5121282	1231303	80.62	202834242	83176133	31.93	13.09	87.22
A549	4	58651	4666773	1093439	81.02	188881416	77523105	32.79	13.46	79.57
A549	5	58639	4696924	1111087	80.87	189555867	75199143	32.64	12.95	80.10

Experiment	Barcodes	Counts	Average counts	Assigned barcodes	Assigned counts	Average assigned counts	Fraction assigned barcodes	Fraction assigned counts
A549_1_DNA	15667758	299222797	19.10	9523291	251677049	26.43	0.61	0.84
A549_2_DNA	15667758	299222797	19.10	9523291	251677049	26.43	0.61	0.84
A549_3_DNA	15667758	299222797	19.10	9523291	251677049	26.43	0.61	0.84
A549_4_DNA	15667758	299222797	19.10	9523291	251677049	26.43	0.61	0.84
A549_5_DNA	15667758	299222797	19.10	9523291	251677049	26.43	0.61	0.84
A549_1_RNA	7637312	95973168	12.57	5146017	79456373	15.44	0.67	0.83
A549_2_RNA	7707693	103808893	13.47	5067807	85879123	16.95	0.66	0.83
A549_3_RNA	7658028	85918859	11.22	5191145	71064019	13.69	0.68	0.83
A549_4_RNA	6935335	80063496	11.54	4726312	66159992	14.00	0.68	0.83
A549_5_RNA	6998535	77706392	11.10	4758105	64312175	13.52	0.68	0.83

Histograms barcodes per oligo, counts per barcode

Histogramm of number of barcodes per oligo and the number of counts per barcode devidied by DNA and RNA. Median is red, mean is blue.

Activity

Violin and box plots of the log2 fold change of all oligos by the assay. Grouped by labels if set, otherwise NA. First tab shows plots using (in average) 54115 oligos with a minimum number of 10 barcodes. Second tab shows all 58442 oligos that have assigned barcodes.

--- title: "MPRAsnakeflow experiment QC report" page-layout: full format: html: code-fold: true code-tools: true embed-resources: true anchor-sections: true smooth-scroll: true toc: true theme: light: flatly dark: darkly jupyter: python3 --- ```{python} #| echo: false # Imports from IPython.display import display, Image, Markdown import pandas as pd import json ``` ```{python} #| tags: [parameters] #| echo: false ``` ```{python} #| echo: false oligo_cor_merged_table_thresh = pd.read_csv(f"{workdir}/{statistics_all_oligo_cor_thresh}", sep='\t') oligo_cor_merged_table_all = pd.read_csv(f"{workdir}/{statistics_all_oligo_cor_all}", sep='\t') dna_spear = oligo_cor_merged_table_thresh['DNA_spearman'].min() rna_spear = oligo_cor_merged_table_thresh['RNA_spearman'].min() ratio_spear = oligo_cor_merged_table_thresh['Ratio_spearman'].min() ``` ```{python} #| echo: false threshold_dna_spear = 0.85 threshold_rna_spear = 0.95 threshold_ratio_spear = 0.75 important = dna_spear < threshold_dna_spear and rna_spear < threshold_rna_spear and ratio_spear < threshold_ratio_spear warning = dna_spear < threshold_dna_spear or rna_spear < threshold_rna_spear or ratio_spear < threshold_ratio_spear if important: display(Markdown(f''' ::: {"{.callout-important}"} ## Low correlation! Spearman correlation across replicates is low using a barcode threshold per oligo of {thresh}! Spearman correlation of DNA is {dna_spear:.2f}, RNA is {rna_spear:.2f} and DNA/RNA ratio is {ratio_spear:.2f}. Minimum allowed values are {threshold_dna_spear:.2f}, {threshold_rna_spear:.2f}, and {threshold_ratio_spear:.2f}. ::: ''')) elif warning: display(Markdown(f''' ::: {"{.callout-warning}"} ## Low correlation warning! At least one (not all) Spearman correlations across replicates is low using a barcode threshold per oligo of {thresh}! Spearman correlation of DNA is {dna_spear:.2f}, RNA is {rna_spear:.2f} and DNA/RNA ratio is {ratio_spear:.2f}. Minimum allowed values are {threshold_dna_spear:.2f}, {threshold_rna_spear:.2f}, and {threshold_ratio_spear:.2f}. ::: ''')) else: display(Markdown(f''' ::: {"{.callout-tip}"} ## Good Spearman correlation across replicates! The data has a good Spearman correlations across replicates using a barcode threshold per oligo of {thresh}! Spearman correlation of DNA is {dna_spear:.2f}, RNA is {rna_spear:.2f} and DNA/RNA ratio is {ratio_spear:.2f}. ::: ''')) ``` # Overall quality metrics <details> <summary>Table explanation</summary> - **median rna read count:** Median of RNA read count for oligos that passed filtering to determine sufficient coverage in terms of read count. Value is the median of all replicates. - **median barcodes passing filtering:** Median number of barcodes across tested sequences that passed filtering to determine if there was sufficient barcode to oligo coverage. Value is the median of all replicates. - **pearson correlation:** The correlation of log2 RNA/DNA ratios across tested sequences as a measure of replicable activity signal. Value is the median of replicate comparisons using only oligos with >= `{python} thresh` barcodes. - **fraction oligos passing:** Fraction of tested sequences that passed filtering of the mappable sequences to determine if the designed library was sufficiently recovered. Value is the median of all replicates and using only oligos with >= `{python} thresh` barcodes. </details> ```{python} #| echo: false with open(f"{workdir}/{qc_metrics_file}", 'r') as file: qc_data = json.load(file) df_qc = pd.DataFrame([qc_data]) df_qc.columns = df_qc.columns.str.replace("_", " ", regex=False) #df_qc.columns = ['Value'] df_qc.style.hide(axis="index").format(precision=2) ``` # DNA over RNA counts Plotting normalized counts of DNA vs RNA (median across replicates). Only oligos within all replicates are shown. We should see a variation within the RNA count data (along the y axis). If count data between RNA and DNA is highly correlated (e.g. follows the identity line) there is no variation between designed oligos. This is an indication that RNA is inflated with DNA and the DNA digestion before creating cDNA did not work as expected. ::: {.panel-tabset} ## Threshold `{python} thresh` ```{python} #| echo: false Image(f"{workdir}/{dna_over_rna_thresh_plot}") ``` ## All ```{python} #| echo: false Image(f"{workdir}/{dna_over_rna_plot}") ``` ::: # Oligo correlation Oligo correlation plots of DNA, RNA and DNA/RNA ratios across replicates. First tab shows plots using (in average) `{python} "%d" % oligo_cor_merged_table_thresh['number_Oligos_Joined'].mean()` oligos with a minimum number of `{python} thresh` barcodes. Second tab shows all `{python} "%d" % oligo_cor_merged_table_all['number_Oligos_Joined'].mean()` oligos that have assigned barcodes. ```{python} #| echo: false def filter_table(df): df = df.round(2).drop(columns=['DNA_pearson','RNA_pearson', 'Ratio_pearson', 'fraction_Oligos_ReplicateA', 'fraction_Oligos_ReplicateB', 'NormSymmetry']) df.columns = df.columns.str.replace("_", " ", regex=False).str.replace("Replicate", " ", regex=False).str.replace("number ", "#", regex=False) return(df) ``` ::: {.panel-tabset} ## Threshold `{python} thresh` ```{python} #| echo: false oligo_cor_merged_table_thresh_filter = filter_table(oligo_cor_merged_table_thresh) oligo_cor_merged_table_thresh_filter.style.hide(axis="index").format( precision=2) ``` ## All ```{python} #| echo: false oligo_cor_merged_table_all_filter = filter_table(oligo_cor_merged_table_all) oligo_cor_merged_table_all_filter.style.hide(axis="index").format( precision=2) ``` ::: ::: {.panel-tabset} ## Threshold `{python} thresh` ::: {.panel-tabset} ### DNA ```{python} #| echo: false display(Image(f"{workdir}/{dna_oligo_coor_min_thre_plot }")) ``` ### RNA ```{python} #| echo: false display(Image(f"{workdir}/{rna_oligo_coor_min_thre_plot}")) ``` ### Ratio ```{python} #| echo: false display(Image(f"{workdir}/{ratio_oligo_min_thre_plot}")) ``` ::: ## All ::: {.panel-tabset} ### DNA ```{python} #| echo: false display(Image(f"{workdir}/{dna_oligo_coor_plot}")) ``` ### RNA ```{python} #| echo: false display(Image(f"{workdir}/{rna_oligo_coor_plot}")) ``` ### Ratio ```{python} #| echo: false display(Image(f"{workdir}/{ratio_oligo_coor_plot}")) ``` ::: ::: # Experiment statistic ```{python} #| echo: false df_merged = pd.read_csv(f"{workdir}/{statistics_all_merged}", sep='\t').round(2) n_oligos = df_merged['oligos design'].iloc[0] n_barcodes = df_merged['barcodes design'].iloc[0] avg_oligos = df_merged['oligos dna/rna'].mean() avg_matched_barcodes = df_merged['matched barcodes'].mean() avg_unknown_barcodes = df_merged['unknown barcodes dna/rna'].mean() ``` The total number of oligos in this experiment is `{python} f"{n_oligos}"` (defined by the assignment) with `{python} f"{n_barcodes}"` associated barcodes. In average across replicates we see `{python} f"{avg_oligos:.0f}"` from `{python} f"{avg_matched_barcodes:.0f}"` average barcodes in the count data and around `{python} f"{avg_unknown_barcodes:.0f}"` barcodes where not in the assignment. ::: {.panel-tabset} # DNA/RNA merged ```{python} #| echo: false df_merged.drop(columns=['oligos design','barcodes design', 'barcodes dna/rna'], inplace=True) df_merged.style.hide(axis="index").format( precision=2) ``` # DNA/RNA individual ```{python} #| echo: false df_single = pd.read_csv(f"{workdir}/{statistics_all_single}", sep='\t').round(2) df_single.style.hide(axis="index").format( precision=2) ``` ::: # Histograms barcodes per oligo, counts per barcode Histogramm of number of barcodes per oligo and the number of counts per barcode devidied by DNA and RNA. Median is red, mean is blue. ::: {.panel-tabset} # Number of barcodes per oligo ```{python} #| echo: false display(Image(f"{workdir}/{counts_per_oligo}")) ``` # Number of counts per DNA barcode ```{python} #| echo: false display(Image(f"{workdir}/{counts_per_bc_dna}")) ``` # Number of counts per DNA barcode ```{python} #| echo: false display(Image(f"{workdir}/{counts_per_bc_rna}")) ``` ::: # Activity Violin and box plots of the log2 fold change of all oligos by the assay. Grouped by labels if set, otherwise `NA`. First tab shows plots using (in average) `{python} "%d" % oligo_cor_merged_table_thresh['number_Oligos_Joined'].mean()` oligos with a minimum number of `{python} thresh` barcodes. Second tab shows all `{python} "%d" % oligo_cor_merged_table_all['number_Oligos_Joined'].mean()` oligos that have assigned barcodes. ::: {.panel-tabset} ## Threshold `{python} thresh` ```{python} #| echo: false display(Image(f"{workdir}/{activity_thresh}")) ``` ## All ```{python} #| echo: false display(Image(f"{workdir}/{activity_all}")) ``` :::